Wind and Structures

CONTENTS

Volume 36, Number 6, 2023

• Machine learning-based prediction of wind forces on CAARC standard tall buildings

  Yi Li, Jie-Ting Yin, Fu-Bin Chen and Qiu-Sheng Li

  Abstract | Full Text (2K)

  pages 355-366.

  DOI: 10.12989/was.2023.36.6.355

• Extrapolation of wind pressure for low-rise buildings at different scales using few-shot learning

  Yanmo Weng and Stephanie G. Paal

  Abstract | Full Text (2K)

  pages 367-377.

  DOI: 10.12989/was.2023.36.6.367

• Predicting the lateral displacement of tall buildings using an LSTM-based deep learning approach

  Bubryur Kim, K.R. Sri Preethaa, Zengshun Chen, Yuvaraj Natarajan, Gitanjali Wadhwa and Hong Min Lee

  Abstract | Full Text (2K)

  pages 379-392.

  DOI: 10.12989/was.2023.36.6.379

• Prediction of skewness and kurtosis of pressure coefficients on a low-rise building by deep learning

  Youqin Huang, Guanheng Ou, Jiyang Fu and Huifan Wu

  Abstract | Full Text (2K)

  pages 393-404.

  DOI: 10.12989/was.2023.36.6.393

• A deep learning framework for wind pressure super-resolution reconstruction

  Xiao Chen, Xinhui Dong, Pengfei Lin, Fei Ding, Bubryur Kim, Jie Song, Yiqing Xiao and Gang Hu

  Abstract | Full Text (3K)

  pages 405-421.

  DOI: 10.12989/was.2023.36.6.405

• Prediction of aerodynamic coefficients of streamlined bridge decks using artificial neural network based on CFD dataset

  Severin Tinmitonde, Xuhui He, Lei Yan, Cunming Ma and Haizhu Xiao

  Abstract | Full Text (2K)

  pages 423-434.

  DOI: 10.12989/was.2023.36.6.423